Statistical analysis for engineers and scientists : a computer-based approach
Author(s)
Bibliographic Information
Statistical analysis for engineers and scientists : a computer-based approach
（McGraw-Hill series in industrial engineering and management science）
McGraw-Hill, c1994
- : IBM
- : Mac
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Note
Rev. ed. of: Statistical analysis for engineers. c1988
Includes index
Description and Table of Contents
- Volume
-
: Mac ISBN 9780078396052
Description
This text covers topics such as nonparametric statistics, statistical quality control, multivariate regression analysis and operating characteristic curves. The accompanying MAC software gives a complete treatment of statistically valid sample sizes in all tests of hypotheses addressed.
Table of Contents
- Probability - fundamental concepts and operational rules
- discrete random variables
- continuous random variables
- the mean, variance, expected value operator, and other functions of random variables
- classification and description of sample data
- sampling distributions - random sampling, the sample mean and sample variance, the central limit theorem
- point and interval estimates and the estimation of the mean and variance
- hypothesis tests about a single mean, a single proportion, or a single variance
- hypothesis testing for two means, two variances or two proportions
- fitting equations to data - simple linear regression analysis and curvilinear regression analysis, multivariate regression analysis
- hypothesis tests for two or more means - analysis of variance, single factor designs
- factorial analysis of variance
- an introduction to statistical quality control
- some additional methods of data analysis.
- Volume
-
: IBM ISBN 9780078396083
Description
This text covers topics such as nonparametric statistics, statistical quality control, multivariate regression analysis and operating characteristic curves. The accompanying IBM software gives a complete treatment of statistically valid sample sizes in all tests of hypotheses addressed.
Table of Contents
- Probability - fundamental concepts and operational rules
- discrete random variables
- continuous random variables
- the mean, variance, expected value operator, and other functions of random variables
- classification and description of sample data
- sampling distributions - random sampling, the sample mean and sample variance, the central limit theorem
- point and interval estimates and the estimation of the mean and variance
- hypothesis tests about a single mean, a single proportion, or a single variance
- hypothesis testing for two means, two variances or two proportions
- fitting equations to data - simple linear regression analysis and curvilinear regression analysis, multivariate regression analysis
- hypothesis tests for two or more means - analysis of variance, single factor designs
- factorial analysis of variance
- an introduction to statistical quality control
- some additional methods of data analysis.
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